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古典作业车间调度问题已经被研究了几十年并证明为 NP-hard问题。柔性作业车间调度是古典作业车间调度问题的扩展 ,它允许工序由一个机床集合中的任意一台加工 ,调度的目的是将工序分配给各机床 ,并对各机床上的工序进行排序以使完成所有工序的时间最小化。本文采用遗传算法进行柔性作业车间调度研究 ,针对柔性作业车间问题提出了一种新颖直观的基因编码方法 ,从而取消了运用遗传算法求解作业车间问题时为使基因合法化而进行的基因修复过程 ,仿真结果表明用该遗传算法解决柔性作业车间调度问题是有效的。
Classical job shop scheduling problems have been studied for decades and proved to be NP-hard problems. Flexible job shop scheduling is an extension of the classical job shop scheduling problem that allows a job to be machined from any one of a set of machine tools that is scheduled to be assigned to each machine tool and to sequence the processes on each machine tool to complete All processes are minimized in time. In this paper, genetic algorithm is used to study the flexible job shop scheduling. A novel and intuitive gene coding method is proposed to solve the problem of flexible job shop, which eliminates the gene repair process of genetic algorithm to solve the problem of job shop by genetic algorithm. The simulation results show that the genetic algorithm to solve the problem of flexible job shop scheduling is effective.